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1.  Getting from Genes to Function in Lung Disease 
Genome-wide association studies (GWAS) have revealed novel genes and pathways involved in lung disease, many of which are potential targets for therapy. However, despite numerous successes, a large proportion of the genetic variance in disease risk remains unexplained, and the function of the associated genetic variations identified by GWAS and the mechanisms by which they alter individual risk for disease or pathogenesis are still largely unknown. The National Heart, Lung, and Blood Institute (NHLBI) convened a 2-day workshop to address these shortcomings and to make recommendations for future research areas that will move the scientific community beyond gene discovery. Topics of individual sessions ranged from data integration and systems genetics to functional validation of genetic variations in humans and model systems. There was broad consensus among the participants for five high-priority areas for future research, including the following: (1) integrated approaches to characterize the function of genetic variations, (2) studies on the role of environment and mechanisms of transcriptional and post-transcriptional regulation, (3) development of model systems to study gene function in complex biological systems, (4) comparative phenomic studies across lung diseases, and (5) training in and applications of bioinformatic approaches for comprehensive mining of existing data sets. Last, it was agreed that future research on lung diseases should integrate approaches across “-omic” technologies and to include ethnically/racially diverse populations in human studies of lung disease whenever possible.
PMCID: PMC2949401  PMID: 20558629
genetics; epigenetics; genomics; bioinformatics; lung disease
2.  Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies 
PLoS ONE  2008;3(10):e3583.
A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a “cosmopolitan” tagging approach to capture the genetic diversity across ∼2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.
PMCID: PMC2571995  PMID: 18974833

Results 1-2 (2)